A Bayesian spatio-temporal statistical analysis of Out-of-Hospital Cardiac Arrests
Type
ArticleAuthors
Peluso, StefanoMira, Antonietta
Rue, Haavard

Tierney, Nicholas John
Benvenuti, Claudio
Cianella, Roberto
Caputo, Maria Luce
Auricchio, Angelo
KAUST Department
Statistics ProgramComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Date
2020-02-03Online Publication Date
2020-02-03Print Publication Date
2020-07Embargo End Date
2021-01-20Permanent link to this record
http://hdl.handle.net/10754/661091
Metadata
Show full item recordAbstract
We propose a Bayesian spatio-temporal statistical model for predicting Out-of-Hospital Cardiac Arrests (OHCA). Risk maps for Ticino, adjusted for demographic covariates, are built for explaining and forecasting the spatial distribution of OHCAs and their temporal dynamics. The occurrence intensity of the OHCA event in each area of interest, and the cardiac risk-based clustering of municipalities are efficiently estimated, through a statistical model that decomposes OHCA intensity into overall intensity, demographic fixed effects, spatially structured and unstructured random effects, time polynomial dependence and spatio-temporal random effect. In the studied geography, time evolution and dependence on demographic features are robust over different categories of OHCAs, but with variability in their spatial and spatio-temporal structure. Two main OHCA incidence-based clusters of municipalities are identified.Citation
Peluso, S., Mira, A., Rue, H., Tierney, N. J., Benvenuti, C., Cianella, R., … Auricchio, A. (2020). A Bayesian spatiotemporal statistical analysis of out-of-hospital cardiac arrests. Biometrical Journal, 62(4), 1105–1119. doi:10.1002/bimj.201900166Sponsors
Financial support from Fondazione Fratelli Agostino Enrico Rocca is acknowledged. Antonietta Mira was partially supported by SNF grant 105218 166504. The authors thank the Swiss Cardiology Foundation.Publisher
WileyJournal
Biometrical Journalae974a485f413a2113503eed53cd6c53
10.1002/bimj.201900166